Create a connection with Shopify (via Deep Data integration)

The Deep Data integration with Shopify is possible with a MailBlue Plus or Professional subscription. It connects information about a purchase, but also directly transfers an abandoned cart from Shopify to MailBlue. This data can be used to send personalized follow-up emails to your contacts and create segmented lists.

How does the integration work?

Discover the power of personalized marketing. Thanks to the integration between MailBlue and Shopify, you can start with more personalized and targeted communication in just a few seconds. Through this integration, you can seamlessly transfer data from Shopify to MailBlue. Build a better relationship with your customers by providing them with an optimal user experience and generate more sales.

For example, you can use start triggers in MailBlue based on order data, memberships, or events, and then perform A/B tests, create splits, and/or filter based on certain properties within MailBlue to personalize and optimize the contact with your customers.


Based on collected data, you can optimize your marketing processes, for instance, by sending a different email to everyone with gender 'female' in your contacts or by sending different emails for order 'X' than contacts with gender 'male' or purchase of product 'Y'. In MailBlue, you can also choose to send emails with a specific offer at the most suitable time for that contact by using predictive sending.

How do I set up the integration?

  1. Go to the bottom left of your MailBlue account and navigate to 'Settings > Integrations'.
  2. Click on 'Add an integration' and select 'Shopify'.
  3. You need to accept the new terms of service from Shopify.
  4. Then, enter your Shopify domain name and click on 'Connect'.

You will then be redirected to your Shopify where you will be asked to authorize the connection. From now on, all contacts placing an order or abandoning the shopping cart will be added to your MailBlue account. Additionally, the order status of these contacts will be continuously synchronized from your Shopify account to your MailBlue account.


Importing Past Orders

You can import historical data from your Shopify account into MailBlue. This includes the following data:

  • All contacts in your Shopify account with every order they have placed.
  • All contacts in your Shopify account who have not placed any orders.
  • All orders placed by the contacts already in your MailBlue account.

Good to know: historical data does not trigger automations using the 'Makes a purchase' start trigger.

To import historical data, follow these steps:

  1. Click on 'Settings > Integrations' in the bottom left of the MailBlue menu.
  2. Click on the connected Shopify store and then on 'Manage'.
  3. Click on the 'Sync historical data' button.

Viewing Shopify data in contact information in MailBlue

When contacts are synchronized from the Shopify store via the Deep Data integration, both their orders and abandoned cart data will be displayed in the table under their general contact information in MailBlue:


You can filter the e-commerce activities. If you have multiple Shopify stores linked, you can also filter by shop type next to this box:


Within the e-commerce table, you will find the total revenue from that customer, as well as the total number of orders placed and total number of products purchased. Below, you will find the following information:

  • Order number
  • Total order price
  • Order date and time
  • Order status (completed or abandoned)
  • Possibly: name of the respective Shopify store

By clicking on the 'Products' button, you will see the further order details on the right. This will show which exact product(s) are involved.


Thanks to all the data transferred from Shopify to MailBlue, you can extensively segment within MailBlue based on various conditions. This helps you create segments and you can also use these conditions to make splits in your automations based on them:

  • Total revenue
  • Total number of orders
  • Total number of products
  • Last order date
  • Last order price
  • Last order currency
  • Last order shipping method
  • Last order product count
  • Last product ID
  • Last product SKU
  • Last product name
  • Last product category
  • Order date
  • Order time
  • Product name in random order
  • Product category in random order
  • Shipping method in random order
  • Currency in random order
  • Product ID in random order
  • Product SKU in each order
  • Has made a purchase
  • Has not made a purchase
  • Has subscribed to marketing
  • Has not subscribed to marketing
  • Has abandoned cart
  • Has not abandoned cart
  • Recovered abandoned cart
  • Did not recover abandoned cart
  • Total value of last abandoned cart
  • Number of products in last abandoned cart
  • Product name in last abandoned cart
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